Upgrading nirmatrelvir to inhibit SARS-CoV-2 Mpro via DeepFrag and free energy calculations

The first oral drug for the treatment of COVID-19, Paxlovid, has been authorized; however, nirmatrelvir, a major component of the drug, is reported to be associated with some side effects. Moreover, the appearance of many novel variants raises concerns about drug resistance, and designing new potent inhibitors to prevent viral replication is thus urgent. In this context, using a hybrid approach combining machine learning (ML) and free energy simulations, 6 compounds obtained by modifying nirmatrelvir were proposed to bind strongly to SARS-CoV-2 Mpro. The structural modification of nirmatrelvir significantly enhances the electrostatic interaction free energy between the protein and ligand and slightly decreases the vdW term. However, the vdW term is the most important factor in controlling the ligand-binding affinity. In addition, the modified nirmatrelvir might be less toxic to the human body than the original inhibitor.

Morphology of a Transmembrane Aβ42 Tetramer via REMD Simulations

The folding/misfolding of membrane-permiable Amyloid beta (Aβ) peptides is likely associated with the advancing stage of Alzheimer's disease (AD) by disrupting Ca²⁺ homeostasis. In this context, the aggregation of four transmembrane Aβ_17-42 peptides was investigated using temperature replica-exchange molecular dynamics (REMD) simulations. The obtained results indicated that the secondary structure of transmembrane Aβ peptides tends to have different propensities compared to those in solution. Interestingly, the residues favorably forming β-structure were interleaved by residues rigidly adopting turn-structure. A combination of β and turn regions likely forms a pore structure. Six morphologies of 4Aβ were found over the free energy landscape and clustering analyses. Among these, the morphologies include (1) Aβ binding onto the membrane surface and three transmembrane Aβ; (2) three helical and coil transmembrane Aβ; (3) four helical transmembrane Aβ; (4) three helical and one β-hairpin transmembrane Aβ; (5) two helical and two β-strand transmembrane Aβ; and (6) three β-strand and one helical transmembrane Aβ. Although the formation of the β-barrel structure was not observed during the 0.28 ms─long MD simulation, the structure is likely to form when the simulation time is further extended.

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations

Inhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R=0.748±0.044. Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine compounds from the top 100 ML inhibitors were suggested to bind well to the protease with the domination of van der Waals interactions. Furthermore, the binding affinity of these compounds is also higher than that of nirmatrelvir, which was recently approved by the US FDA to treat COVID-19. In addition, the ligands altered the catalytic triad Cys145 - His41 - Asp187, possibly disturbing the biological activity of SARS-CoV-2.

Characterizing the ligand-binding affinity toward SARS-CoV-2 Mpro via physics- and knowledge-based approaches

Computational approaches, including physics- and knowledge-based methods, have commonly been used to determine the ligand-binding affinity toward SARS-CoV-2 main protease (Mpro or 3CLpro). Strong binding ligands can thus be suggested as potential inhibitors for blocking the biological activity of the protease. In this context, this paper aims to provide a short review of computational approaches that have recently been applied in the search for inhibitor candidates of Mpro. In particular, molecular docking and molecular dynamics (MD) simulations are usually combined to predict the binding affinity of thousands of compounds. Quantitative structure-activity relationship (QSAR) is the least computationally demanding and therefore can be used for large chemical collections of ligands. However, its accuracy may not be high. Moreover, the quantum mechanics/molecular mechanics (QM/MM) method is most commonly used for covalently binding inhibitors, which also play an important role in inhibiting the activity of SARS-CoV-2. Furthermore, machine learning (ML) models can significantly increase the searching space of ligands with high accuracy for binding affinity prediction. Physical insights into the binding process can then be confirmed via physics-based calculations. Integration of ML models into computational chemistry provides many more benefits and can lead to new therapies sooner.

Correction: Rapid prediction of possible inhibitors for SARS-CoV-2 main protease using docking and FPL simulations

[This corrects the article DOI: 10.1039/D0RA06212J.].

Distal Hydrophobic Loop Modulates the Copper Active Site and Reaction of AA13 Polysaccharide Monooxygenases

Polysaccharide monooxygenases (PMOs) use a type-2 copper center to activate O₂ for the selective hydroxylation of one of the two C-H bonds of glycosidic linkages. Our electron paramagnetic resonance (EPR) analysis and molecular dynamics (MD) simulations suggest the unprecedented dynamic roles of the loop containing the residue G89 (G89 loop) on the active site structure and reaction cycle of starch-active PMOs (AA13 PMOs). In the Cu(II) state, the G89 loop could switch between an "open" and "closed" conformation, which is associated with the binding and dissociation of an aqueous ligand in the distal site, respectively. The conformation of the G89 loop influences the positioning of the copper center on the preferred substrate of AA13 PMOs. The dissociation of the distal ligand results in the bending of the T-shaped core of the Cu(II) active site, which could help facilitate its reduction to the active Cu(I) state. In the Cu(I) state, the G89 loop is in the "closed" conformation with a confined copper center, which could allow for efficient O₂ binding. In addition, the G89 loop remains in the "closed" conformation in the Cu(II)-superoxo intermediate, which could prevent off-pathway superoxide release via exchange with the distal aqueous ligand. Finally, at the end of the reaction cycle, aqueous ligand binding to the distal site could switch the G89 loop to the "open" conformation and facilitate product release.

Transcriptomic and Ultrastructural Analyses of Pyricularia Oryzae Treated With Fungicidal Peptaibol Analogs of Trichoderma Trichogin

Eco-friendly analogs of Trichogin GA IV, a short peptaibol produced by Trichoderma longibrachiatum, were assayed against Pyricularia oryzae, the causal agent of rice blast disease. In vitro and in vivo screenings allowed us to identify six peptides able to reduce by about 70% rice blast symptoms. One of the most active peptides was selected for further studies. Microscopy analyses highlighted that the treated fungal spores could not germinate and the fluorescein-labeled peptide localized on the spore cell wall and in the agglutinated cytoplasm. Transcriptomic analysis was carried out on P. oryzae mycelium 3 h after the peptide treatment. We identified 1,410 differentially expressed genes, two-thirds of which upregulated. Among these, we found genes involved in oxidative stress response, detoxification, autophagic cell death, cell wall biogenesis, degradation and remodeling, melanin and fatty acid biosynthesis, and ion efflux transporters. Molecular data suggest that the trichogin analogs cause cell wall and membrane damages and induce autophagic cell death. Ultrastructure observations on treated conidia and hyphae confirmed the molecular data. In conclusion, these selected peptides seem to be promising alternative molecules for developing effective bio-pesticides able to control rice blast disease.

Improving ligand-ranking of AutoDock Vina by changing the empirical parameters

AutoDock Vina (Vina) achieved a very high docking-success rate, p ^ , but give a rather low correlation coefficient, R , for binding affinity with respect to experiments. This low correlation can be an obstacle for ranking of ligand-binding affinity, which is the main objective of docking simulations. In this context, we evaluated the dependence of Vina R coefficient upon its empirical parameters. R is affected more by changing the gauss2 and rotation than other terms. The docking-success rate p ^ is sensitive to the alterations of the gauss1, gauss2, repulsion, and hydrogen bond parameters. Based on our benchmarks, the parameter set1 has been suggested to be the most optimal. The testing study over 800 complexes indicated that the modified Vina provided higher correlation with experiment R set 1 = 0.556 ± 0.025 compared with R Default = 0.493 ± 0.028 obtained by the original Vina and R Vina 1.2 = 0.503 ± 0.029 by Vina version 1.2. Besides, the modified Vina can be also applied more widely, giving R ≥ 0.500 for 32/48 targets, compared with the default package, giving R ≥ 0.500 for 31/48 targets. In addition, validation calculations for 1036 complexes obtained from version 2019 of PDBbind refined structures showed that the set1 of parameters gave higher correlation coefficient ( R set 1 = 0.617 ± 0.017 ) than the default package ( R Default = 0.543 ± 0.020 ) and Vina version 1.2 ( R Vina 1.2 = 0.540 ± 0.020 ). The version of Vina with set1 of parameters can be downloaded at https://github.com/sontungngo/mvina. The outcomes would enhance the ranking of ligand-binding affinity using Autodock Vina.

Binding of inhibitors to the monomeric and dimeric SARS-CoV-2 Mpro

SARS-CoV-2 rapidly infects millions of people worldwide since December 2019. There is still no effective treatment for the virus, resulting in the death of more than one million patients. Inhibiting the activity of SARS-CoV-2 main protease (Mpro), 3C-like protease (3CLP), is able to block the viral replication and proliferation. In this context, our study has revealed that in silico screening for inhibitors of SARS-CoV-2 Mpro can be reliably done using the monomeric structure of the Mpro instead of the dimeric one. Docking and fast pulling of ligand (FPL) simulations for both monomeric and dimeric forms correlate well with the corresponding experimental binding affinity data of 24 compounds. The obtained results were also confirmed via binding pose and noncovalent contact analyses. Our study results show that it is possible to speed up computer-aided drug design for SARS-CoV-2 Mpro by focusing on the monomeric form instead of the larger dimeric one.

Computational Determination of Potential Inhibitors of SARS-CoV-2 Main Protease

The novel coronavirus (SARS-CoV-2) has infected several million people and caused thousands of deaths worldwide since December 2019. As the disease is spreading rapidly all over the world, it is urgent to find effective drugs to treat the virus. The main protease (Mpro) of SARS-CoV-2 is one of the potential drug targets. Therefore, in this context, we used rigorous computational methods, including molecular docking, fast pulling of ligand (FPL), and free energy perturbation (FEP), to investigate potential inhibitors of SARS-CoV-2 Mpro. We first tested our approach with three reported inhibitors of SARS-CoV-2 Mpro, and our computational results are in good agreement with the respective experimental data. Subsequently, we applied our approach on a database of ∼4600 natural compounds, as well as 8 available HIV-1 protease (PR) inhibitors and an aza-peptide epoxide. Molecular docking resulted in a short list of 35 natural compounds, which was subsequently refined using the FPL scheme. FPL simulations resulted in five potential inhibitors, including three natural compounds and two available HIV-1 PR inhibitors. Finally, FEP, the most accurate and precise method, was used to determine the absolute binding free energy of these five compounds. FEP results indicate that two natural compounds, cannabisin A and isoacteoside, and an HIV-1 PR inhibitor, darunavir, exhibit a large binding free energy to SARS-CoV-2 Mpro, which is larger than that of 13b, the most reliable SARS-CoV-2 Mpro inhibitor recently reported. The binding free energy largely arises from van der Waals interaction. We also found that Glu166 forms H-bonds to all of the inhibitors. Replacing Glu166 by an alanine residue leads to ∼2.0 kcal/mol decreases in the affinity of darunavir to SARS-CoV-2 Mpro. Our results could contribute to the development of potential drugs inhibiting SARS-CoV-2.

Assessing potential inhibitors of SARS-CoV-2 main protease from available drugs using free energy perturbation simulations

The main protease (Mpro) of the novel coronavirus SARS-CoV-2, which has caused the COVID-19 pandemic, is responsible for the maturation of its key proteins. Thus, inhibiting SARS-CoV-2 Mpro could prevent SARS-CoV-2 from multiplying. Because new inhibitors require thorough validation, repurposing current drugs could help reduce the validation process. Many recent studies used molecular docking to screen large databases for potential inhibitors of SARS-CoV-2 Mpro. However, molecular docking does not consider molecular dynamics and thus can be prone to error. In this work, we developed a protocol using free energy perturbation (FEP) to assess the potential inhibitors of SARS-CoV-2 Mpro. First, we validated both molecular docking and FEP on a set of 11 inhibitors of SARS-CoV-2 Mpro with experimentally determined inhibitory data. The experimentally deduced binding free energy exhibits significantly stronger correlation with that predicted by FEP (R = 0.94 ± 0.04) than with that predicted by molecular docking (R = 0.82 ± 0.08). This result clearly shows that FEP is the most accurate method available to predict the binding affinity of SARS-CoV-2 Mpro + ligand complexes. We subsequently used FEP to validate the top 33 compounds screened with molecular docking from the ZINC15 database. Thirteen of these compounds were predicted to bind strongly to SARS-CoV-2 Mpro, most of which are currently used as drugs for various diseases in humans. Notably, delamanid, an anti-tuberculosis drug, was predicted to inhibit SARS-CoV-2 Mpro in the nanomolar range. Because both COVID-19 and tuberculosis are lung diseases, delamanid has higher probability to be suitable for treating COVID-19 than other predicted compounds. Analysis of the complexes of SARS-CoV-2 Mpro and the top inhibitors revealed the key residues involved in the binding, including the catalytic dyad His14 and Cys145, which is consistent with the structural studies reported recently.

Rapid prediction of possible inhibitors for SARS-CoV-2 main protease using docking and FPL simulations

Originating for the first time in Wuhan, China, the outbreak of SARS-CoV-2 has caused a serious global health issue. An effective treatment for SARS-CoV-2 is still unavailable. Therefore, in this study, we have tried to predict a list of potential inhibitors for SARS-CoV-2 main protease (Mpro) using a combination of molecular docking and fast pulling of ligand (FPL) simulations. The approaches were initially validated over a set of eleven available inhibitors. Both Autodock Vina and FPL calculations produced consistent results with the experiments with correlation coefficients of R Dock = 0.72 ± 0.14 and R W = -0.76 ± 0.10, respectively. The combined approaches were then utilized to predict possible inhibitors that were selected from a ZINC15 sub-database for SARS-CoV-2 Mpro. Twenty compounds were suggested to be able to bind well to SARS-CoV-2 Mpro. Among them, five top-leads are periandrin V, penimocycline, cis-p-Coumaroylcorosolic acid, glycyrrhizin, and uralsaponin B. The obtained results could probably lead to enhance the COVID-19 therapy.

Nano-plastics and their analytical characterisation and fate in the marine environment: From source to sea

Polymer contamination is a major pollutant in all waterways and a significant concern of the 21st Century, gaining extensive research, media, and public attention. The polymer pollution problem is so vast; plastics are now observed in some of the Earth's most remote regions such as the Mariana trench. These polymers enter the waterways, migrate, breakdown; albeit slowly, and then interact with the environment and the surrounding biodiversity. It is these biodiversity and ecosystem interactions that are causing the most nervousness, where health researchers have demonstrated that plastics have entered the human food chain, also showing that plastics are damaging organisms, animals, and plants. Many researchers have focused on reviewing the macro and micro-forms of these polymer contaminants, demonstrating a lack of scientific data and also a lack of investigation regarding nano-sized polymers. It is these nano-polymers that have the greatest potential to cause the most harm to our oceans, waterways, and wildlife. This review has been especially ruthless in discussing nano-sized polymers, their ability to interact with organisms, and the potential for these nano-polymers to cause environmental damage in the marine environment. This review details the breakdown of macro-, micro-, and nano-polymer contamination, examining the sources, the interactions, and the fates of all of these polymer sizes in the environment. The main focus of this review is to perform a comprehensive examination of the literature of the interaction of nanoplastics with organisms, soils, and waters; followed by the discussion of toxicological issues. A significant focus of the review is also on current analytical characterisation techniques for nanoplastics, which will enable researchers to develop protocols for nanopolymer analysis and enhance understanding of nanoplastics in the marine environment.

Fine Tuning of the Copper Active Site in Polysaccharide Monooxygenases

Type 2 copper active sites, one of the several important copper active sites in biology, were recently found in the novel superfamily of polysaccharide monooxygenases (PMOs) that cleave recalcitrant polysaccharides via an unprecedented oxidative mechanism. The copper center in PMOs is ligated by the bidentate N-terminal histidine residue and another conserved histidine residue, forming a unique T-shaped core termed as Histidine brace. This core serves as the foundation for diverse structures and electronic properties among PMO families and subfamilies. Understanding of the copper active site in PMOs is limited to the static solid structures obtained with X-ray diffraction (XRD), whereas in several families, the copper center exists as a mixture of species in solution as indicated by electron paramagnetic resonance (EPR) spectroscopy. To obtain further details on the copper active sites in PMOs, we carried out density functional theory calculations and molecular dynamics simulations on MtPMO3* that were previously studied with XRD, EPR, mutagenesis, and activity assays. The results reveal the fine-tuning of the binding of the distal ligands by both proximal and distal H-bond-forming residues. Q167 forms H bonds with the proximal O_Tyr ligand of Y167 and the equatorial aqueous ligand (O_eq). T74 forms a H bond with the distal aqueous ligand (O_dis). Removing these H bonds by mutating Q167 or T74 to alanine results in great fluctuations of the axial ligands. Strengthening the proximal H bonds by mutating Q167 to glutamate confines Y167 to the copper centers. In all mutants, the residence time of O_dis is significantly reduced. Q167A, Q167E, and T74A mutants were previously shown to have a significantly reduced activity. Our results indicate that well-tuned H bonds are required for the activity of PMOs.

Impact of the Astaxanthin, Betanin, and EGCG Compounds on Small Oligomers of Amyloid Aβ40 Peptide

There is experimental evidence that the astaxanthin, betanin, and epigallocatechin-3-gallate (EGCG) compounds slow down the aggregation kinetics and the toxicity of the amyloid-β (Aβ) peptide. How these inhibitors affect the self-assembly at the atomic level remains elusive. To address this issue, we have performed for each ligand atomistic replica exchange molecular dynamic (REMD) simulations in an explicit solvent of the Aβ_11-40 trimer from the U-shape conformation and MD simulations starting from Aβ_1-40 dimer and tetramer structures characterized by different intra- and interpeptide conformations. We find that the three ligands have similar binding free energies on small Aβ₄₀ oligomers but very distinct transient binding sites that will affect the aggregation of larger assemblies and fibril elongation of the Aβ₄₀ peptide.

C-Terminal Plays as the Possible Nucleation of the Self-Aggregation of the S-Shape Aβ11-42 Tetramer in Solution: Intensive MD Study

Amyloid beta (Aβ) peptides are characterized as the major factors associated with neuron death in Alzheimer's disease, which is listed as the most common form of neurodegeneration. Disordered Aβ peptides are released from proteolysis of the amyloid precursor protein. The Aβ self-assembly process roughly takes place via five steps: disordered forms → oligomers → photofibrils → mature fibrils → plaques. Although Aβ fibrils are often observed in patient brains, oligomers were recently indicated to be major neurotoxic elements. In this work, the neurotoxic compound S-shape Aβ11-42 tetramer (S4Aβ11-42) was investigated over 10 μs of unbiased MD simulations. In particular, the S4Aβ11-42 oligomer adopted a high dynamics structure, resulting in unsuccessful determination of their structures in experiments. The C-terminal was suggested as the possible nucleation of the Aβ42 aggregation. The sequences 27-35 and 39-40 formed rich β-content, whereas other residues mostly adopted coil structures. The mean value of the β-content over the equilibrium interval is ∼42 ± 3%. Furthermore, the dissociation free energy of the S4Aβ11-42 peptide was predicted using a biased sampling method. The obtained free energy is ΔG US = -58.44 kcal/mol which is roughly the same level as the corresponding value of the U-shape Aβ17-42 peptide. We anticipate that the obtained S4Aβ11-42 structures could be used as targets for AD inhibitor screening over the in silico study.

Substrate selectivity in starch polysaccharide monooxygenases

Degradation of polysaccharides is central to numerous biological and industrial processes. Starch-active polysaccharide monooxygenases (AA13 PMOs) oxidatively degrade starch and can potentially be used with industrial amylases to convert starch into a fermentable carbohydrate. The oxidative activities of the starch-active PMOs from the fungi Neurospora crassa and Myceliophthora thermophila, NcAA13 and MtAA13, respectively, on three different starch substrates are reported here. Using high-performance anion-exchange chromatography coupled with pulsed amperometry detection, we observed that both enzymes have significantly higher oxidative activity on amylose than on amylopectin and cornstarch. Analysis of the product distribution revealed that NcAA13 and MtAA13 more frequently oxidize glycosidic linkages separated by multiples of a helical turn consisting of six glucose units on the same amylose helix. Docking studies identified important residues that are involved in amylose binding and suggest that the shallow groove that spans the active-site surface of AA13 PMOs favors the binding of helical amylose substrates over nonhelical substrates. Truncations of NcAA13 that removed its native carbohydrate-binding module resulted in diminished binding to amylose, but truncated NcAA13 still favored amylose oxidation over other starch substrates. These findings establish that AA13 PMOs preferentially bind and oxidize the helical starch substrate amylose. Moreover, the product distributions of these two enzymes suggest a unique interaction with starch substrates.

Adequate prediction for inhibitor affinity of Aβ40 protofibril using the linear interaction energy method

The search for efficient inhibitors targeting Aβ oligomers and fibrils is an important issue in Alzheimer's disease treatment. As a consequence, an accurate and computationally cheap approach to estimate the binding affinity for many ligands interacting with Aβ peptides is very important. Here, the calculated binding free energies of 30 ligands interacting with 12Aβ11-40 peptides using the linear interaction energy (LIE) approach are found to be in good correlation with experimental data (R = 0.79). The binding affinities of these complexes are also calculated by using free energy perturbation (FEP) and molecular mechanic/Poisson-Boltzmann surface area (MM/PBSA) methods. The time-consuming FEP method provides results with similar correlation (R = 0.72), whereas MM/PBSA calculations show very low correlation with experimental data (R = 0.27). In all complexes, van der Waals interactions contribute much more than electrostatic interactions. The LIE model, which is much less time-consuming than both the FEP and MM/PBSA methods, opens the door to accurate and rapid affinity prediction of ligands with Aβ peptides and the design of new ligands.

Effective Estimation of Ligand-Binding Affinity Using Biased Sampling Method

The binding between two biomolecules is one of the most critical factors controlling many bioprocesses. Therefore, it is of great interest to derive a reliable method to calculate the free binding energy between two biomolecules. In this work, we have demonstrated that the binding affinity of ligands to proteins can be determined through biased sampling simulations. The umbrella sampling (US) method was applied on 20 protein-ligand complexes, including the cathepsin K (CTSK), type II dehydroquinase (DHQase), heat shock protein 90 (HSP90), and factor Xa (FXa) systems. The ligand-binding affinity was evaluated as the difference between the largest and smallest values of the free-energy curve, which was obtained via a potential of mean force analysis. The calculated affinities differ sizably from the previously reported experimental values, with an average difference of ∼3.14 kcal/mol. However, the calculated results are in good correlation with the experimental data, with correlation coefficients of 0.76, 0.87, 0.96, and 0.97 for CTSK, DHQase, HSP90, and FXa, respectively. Thus, the binding free energy of a new ligand can be reliably estimated using our US approach. Furthermore, the root-mean-square errors (RMSEs) of binding affinity of these systems are 1.13, 0.90, 0.37, and 0.25 kcal/mol, for CTSK, DHQase, HSP90, and FXa, respectively. The small RMSE values indicate the good precision of the biased sampling method that can distinguish the ligands exhibiting similar binding affinities.

Interaction of carbohydrate binding module 20 with starch substrates

CBM20s are starch-binding domains found in many amylolytic enzymes, including glucoamylase, alpha-amylase, beta-amylases, and a new family of starch-active polysaccharide monooxygenases (AA13 PMOs). Previous studies of CBM20–substrate interaction only concerned relatively small or soluble amylose molecules, while amylolytic enzymes often work on extended chains of insoluble starch molecules. In this study, we utilized molecular simulation techniques to gain further insights into the interaction of CBM20 with substrates of various sizes via its two separate binding sites, termed as BdS1 and BdS2. Results show that substrate binding at BdS1 involving two conserved tryptophan residues is about 2–4 kcal mol⁻¹ stronger than that at BdS2. CBM20 exhibits about two-fold higher affinity for helical substrates than for the amylose random coils. The affinity for amylose individual double helices does not depend on the helices' length. At least three parallel double helices are required for optimal binding. The binding affinity for a substrate containing 3 or more double helices is ∼−15 kcal mol⁻¹, which is 2–3 kcal mol⁻¹ larger than that for individual double helices. 100 ns molecular dynamics simulations were carried out for the binding of CBM20 to an extended substrate containing 3 layers of 9 60-unit double helices (A3L). A stable conformation of CBM20–A3L was found at BdS1. However, when CBM20 binds A3L viaBdS2, it moves across the surface of the substrate and does not form a stable complex. MD simulations show that small amylose helices are quickly disrupted upon binding to CBM20. Our results provide some important molecular insights into the interactions of CBM20 with starch substrates, which will serve as the basis for further studies of CBM20-containing enzymes, including AA13 PMOs.

CBM20 quickly disrupts small helical amylose substrates and exhibits optimal binding affinity when the substrate has three or more parallel double helices.

Atomistic investigation of an Iowa Amyloid-β trimer in aqueous solution

The self-assembly of Amyloid beta (Aβ) peptides are widely accepted to associate with Alzheimer's disease (AD) via several proposed mechanisms. Because Aβ oligomers exist in a complicated environment consisting of various forms of Aβ, including oligomers, protofibrils, and fibrils, their structure has not been well understood. The negatively charged residue D23 is one of the critical residues of the Aβ peptide as it is located in the central hydrophobic domain of the Aβ N-terminal and forms a salt-bridge D23-K28, which helps stabilize the loop domain. In the familial Iowa (D23N) mutant, the total net charge of Aβ oligomers decreases, resulting in the decrease of electrostatic repulsion between D23N Aβ monomers and thus the increase in their self-aggregation rate. In this work, the impact of the D23N mutation on 3Aβ_11–40 trimer was characterized utilizing temperature replica exchange molecular dynamics (REMD) simulations. Our simulation reveals that D23N mutation significantly enhances the affinity between the constituting chains in the trimer, increases the β-content (especially in the sequence 21–23), and shifts the β-strand hydrophobic core from crossing arrangement to parallel arrangement, which is consistent with the increase in self-aggregation rate. Molecular docking indicates that the Aβ fibril-binding ligands bind to the D23N and WT forms at different poses. These compounds prefer to bind to the N-terminal β-strand of the D23N mutant trimer, while they mostly bind to the N-terminal loop region of the WT. It is important to take into account the difference in the binding of ligands to mutant and wild type Aβ peptides in designing efficient inhibitors for various types of AD.

Amyloid beta peptide oligomers are believed to play key roles in Alzheimer's disease pathogenesis. D23N mutation significantly changes their structure and how they bind potential inhibitors.

In silico studies of solvated F19W amyloid β (11–40) trimer

REMD studies shows that F19W mutation does not change in the overall structure of Aβ_11–40 trimer significantly but increases it flexibility, consistent with the observed formation of the same fibril structures at slower rates.

X-ray absorption spectroscopic characterization of the diferric-peroxo intermediate of human deoxyhypusine hydroxylase in the presence of its substrate eIF5a

Human deoxyhypusine hydroxylase (hDOHH) is an enzyme that is involved in the critical post-translational modification of the eukaryotic translation initiation factor 5A (eIF5A). Following the conversion of a lysine residue on eIF5A to deoxyhypusine (Dhp) by deoxyhypusine synthase, hDOHH hydroxylates Dhp to yield the unusual amino acid residue hypusine (Hpu), a modification that is essential for eIF5A to promote peptide synthesis at the ribosome, among other functions. Purification of hDOHH overexpressed in E. coli affords enzyme that is blue in color, a feature that has been associated with the presence of a peroxo-bridged diiron(III) active site. To gain further insight into the nature of the diiron site and how it may change as hDOHH goes through the catalytic cycle, we have conducted X-ray absorption spectroscopic studies of hDOHH on five samples that represent different species along its reaction pathway. Structural analysis of each species has been carried out, starting with the reduced diferrous state, proceeding through its O2 adduct, and ending with a diferric decay product. Our results show that the Fe⋯Fe distances found for the five samples fall within a narrow range of 3.4-3.5 Å, suggesting that hDOHH has a fairly constrained active site. This pattern differs significantly from what has been associated with canonical dioxygen activating nonheme diiron enzymes, such as soluble methane monooxygenase and Class 1A ribonucleotide reductases, for which the Fe⋯Fe distance can change by as much as 1 Å during the redox cycle. These results suggest that the O2 activation mechanism for hDOHH deviates somewhat from that associated with the canonical nonheme diiron enzymes, opening the door to new mechanistic possibilities for this intriguing family of enzymes.

Cellulose degradation by polysaccharide monooxygenases

Polysaccharide monooxygenases (PMOs), also known as lytic PMOs (LPMOs), enhance the depolymerization of recalcitrant polysaccharides by hydrolytic enzymes and are found in the majority of cellulolytic fungi and actinomycete bacteria. For more than a decade, PMOs were incorrectly annotated as family 61 glycoside hydrolases (GH61s) or family 33 carbohydrate-binding modules (CBM33s). PMOs have an unusual surface-exposed active site with a tightly bound Cu(II) ion that catalyzes the regioselective hydroxylation of crystalline cellulose, leading to glycosidic bond cleavage. The genomes of some cellulolytic fungi contain more than 20 genes encoding cellulose-active PMOs, suggesting a diversity of biological activities. PMOs show great promise in reducing the cost of conversion of lignocellulosic biomass to fermentable sugars; however, many questions remain about their reaction mechanism and biological function. This review addresses, in depth, the structural and mechanistic aspects of oxidative depolymerization of cellulose by PMOs and considers their biological function and phylogenetic diversity.

An unusual peroxo intermediate of the arylamine oxygenase of the chloramphenicol biosynthetic pathway

Streptomyces venezuelae CmlI catalyzes the six-electron oxygenation of the arylamine precursor of chloramphenicol in a nonribosomal peptide synthetase (NRPS)-based pathway to yield the nitroaryl group of the antibiotic. Optical, EPR, and Mössbauer studies show that the enzyme contains a nonheme dinuclear iron cluster. Addition of O(2) to the diferrous state of the cluster results in an exceptionally long-lived intermediate (t(1/2) = 3 h at 4 °C) that is assigned as a peroxodiferric species (CmlI-peroxo) based upon the observation of an (18)O(2)-sensitive resonance Raman (rR) vibration. CmlI-peroxo is spectroscopically distinct from the well characterized and commonly observed cis-μ-1,2-peroxo (μ-η(1):η(1)) intermediates of nonheme diiron enzymes. Specifically, it exhibits a blue-shifted broad absorption band around 500 nm and a rR spectrum with a ν(O-O) that is at least 60 cm(-1) lower in energy. Mössbauer studies of the peroxo state reveal a diferric cluster having iron sites with small quadrupole splittings and distinct isomer shifts (0.54 and 0.62 mm/s). Taken together, the spectroscopic comparisons clearly indicate that CmlI-peroxo does not have a μ-η(1):η(1)-peroxo ligand; we propose that a μ-η(1):η(2)-peroxo ligand accounts for its distinct spectroscopic properties. CmlI-peroxo reacts with a range of arylamine substrates by an apparent second-order process, indicating that CmlI-peroxo is the reactive species of the catalytic cycle. Efficient production of chloramphenicol from the free arylamine precursor suggests that CmlI catalyzes the ultimate step in the biosynthetic pathway and that the precursor is not bound to the NRPS during this step.

A Mononuclear Carboxylate-Rich Oxoiron(IV) Complex: a Structural and Functional Mimic of TauD Intermediate 'J'

The pentadentate ligand (n)Bu-P2DA (2(b), (n)Bu-P2DA = N-(1',1'-bis(2-pyridyl)pentyl)iminodiacetate) was designed to bind an iron center in a carboxylate-rich environment similar to that found in the active sites of TauD and other α-ketoglutarate-dependent mononuclear non-heme iron enzymes. The iron(II) complex (n)Bu(4)N[Fe(II)(Cl)((n)Bu-P2DA)] (3(b)-Cl) was synthesized and crystallographically characterized to have a 2-pyridine-2-carboxylate donor set in the plane perpendicular to the Fe-Cl bond. Reaction of 3(b)-Cl with N-heterocyclic amines such as pyridine or imidazole yielded the N-heterocyclic amine adducts [Fe(II)(N)((n)Bu-P2DA)]. These adducts in turn reacted with oxo-transfer reagents at -95 °C to afford a short-lived oxoiron(IV) complex [Fe(IV)(O)((n)Bu-P2DA)] (5(b)) in yields as high as 90% depending on the heterocycle used. Complex 5(b) exhibits near-IR absorption features (λ(max) = 770 nm) and Mossbauer parameters (δ = 0.04 mm/s; ΔE(Q) = 1.13 mm/s; D = 27±2 cm(-1)) characteristic of an S = 1 oxoiron(IV) species. Direct evidence for an Fe=O bond of 1.66 Å was found from EXAFS analysis. DFT calculations on 5(b) in its S =1 spin state afforded a geometry-optimized structure consistent with the EXAFS data. They further demonstrated that the replacement of two pyridine donors in [Fe(IV)(O)(N4Py)](2+) (N4Py = N,N-(bis(2-pyridyl)methyl)N-bis(2-pyridylmethyl)amine) with carboxylate donors in 5(b) decreased the energy gap between the ground S = 1 and the excited S = 2 states, reflecting the weaker equatorial ligand field of 5(b) and accounting for its larger D value. Complex 5(b) reacted readily with dihydrotoluene, methyldiphenylphosphine and ferrocene at -60 °C, and in all cases was approximately a 5-fold more reactive oxidant than [Fe(IV)(O)(N4Py)](2+). The reactivity differences between these two complexes may arise from a combination of electronic and steric factors. Carboxylate-rich 5(b) represents the closest structural mimic reported thus far of the oxoiron(IV) intermediate ('J') found in TauD and provides us with vital insights into the role carboxylate ligands play in modulating the spectroscopic and reactivity properties of the non-heme oxoiron(IV) moiety.

Active-site structure of a β-hydroxylase in antibiotic biosynthesis

X-ray absorption and resonance Raman spectroscopies show that CmlA, the β-hydroxylase of the chloramphenicol biosynthetic pathway, contains a (μ-oxo)-(μ-1,3-carboxylato)diiron(III) cluster with 6-coordinate iron centers and 3 - 4 His ligands. This active site is found within a unique β-lactamase fold and is distinct from those of soluble methane monooxygenase and related enzymes that utilize a highly conserved diiron cluster with a 2-His-4-carboxylate ligand set within a 4-helix bundle motif. These structural differences may have an impact on the nature of the activated oxygen species of the reaction cycle.

Characterization of two distinct adducts in the reaction of a nonheme diiron(II) complex with O2

Two [Fe(II)(2)(N-EtHPTB)(mu-O(2)X)](2+) complexes, where N-EtHPTB is the anion of N,N,N'N'-tetrakis(2-benzimidazolylmethyl)-2-hydroxy-1,3-diaminopropane and O(2)X is O(2)PPh(2) (1 x O(2)PPh(2)) or O(2)AsMe(2) (1 x O(2)AsMe(2)), have been synthesized. Their crystal structures both show interiron distances of 3.54 A that arise from a (mu-alkoxo)diiron(II) core supported by an O(2)X bridge. These diiron(II) complexes react with O(2) at low temperatures in MeCN (-40 degrees C) and CH(2)Cl(2) (-60 degrees C) to form long-lived O(2) adducts that are best described as (mu-eta(1):eta(1)-peroxo)diiron(III) species (2 x O(2)X) with nu(O-O) approximately 850 cm(-1). Upon warming to -30 degrees C, 2 x O(2)PPh(2) converts irreversibly to a second (mu-eta(1):eta(1)-peroxo)diiron(III) intermediate (3 x O(2)PPh(2)) with nu(O-O) approximately 900 cm(-1), a value which matches that reported for [Fe(2)(N-EtHPTB)(O(2))(O(2)CPh)](2+) (3 x O(2)CPh) (Dong et al. J. Am. Chem. Soc. 1993, 115, 1851-1859). Mossbauer spectra of 2 x O(2)PPh(2) and 3 x O(2)PPh(2) indicate that the iron centers within each species are antiferromagnetically coupled with J approximately 60 cm(-1), while extended X-ray absorption fine structure analysis reveals interiron distances of 3.25 and 3.47 A for 2 x O(2)PPh(2) and 3 x O(2)PPh(2), respectively. A similarly short interiron distance (3.27 A) is found for 2 x O(2)AsMe(2). The shorter interiron distance associated with 2 x O(2)PPh(2) and 2 x O(2)AsMe(2) is proposed to derive from a triply bridged diiron(III) species with alkoxo (from N-EtHPTB), 1,2-peroxo, and 1,3-O(2)X bridges, while the longer distance associated with 3 x O(2)PPh(2) results from the shift of the O(2)PPh(2) bridge to a terminal position on one iron. The differences in nu(O-O) are also consistent with the different interiron distances. It is suggested that the O...O bite distance of the O(2)X moiety affects the thermal stability of 2 x O(2)X, with the O(2)X having the largest bite distance (O(2)AsMe(2)) favoring the 2 x O(2)X adduct and the O(2)X having the smallest bite distance (O(2)CPh) favoring the 3 x O(2)X adduct. Interestingly, neither 3 x O(2)AsMe(2) nor the benzoate analog of 2 x O(2)X (2 x O(2)Bz) are observed.

Human deoxyhypusine hydroxylase, an enzyme involved in regulating cell growth, activates O2 with a nonheme diiron center

Deoxyhypusine hydroxylase is the key enzyme in the biosynthesis of hypusine containing eukaryotic translation initiation factor 5A (eIF5A), which plays an essential role in the regulation of cell proliferation. Recombinant human deoxyhypusine hydroxylase (hDOHH) has been reported to have oxygen- and iron-dependent activity, an estimated iron/holoprotein stoichiometry of 2, and a visible band at 630 nm responsible for the blue color of the as-isolated protein. EPR, Mössbauer, and XAS spectroscopic results presented herein provide direct spectroscopic evidence that hDOHH has an antiferromagnetically coupled diiron center with histidines and carboxylates as likely ligands, as suggested by mutagenesis experiments. Resonance Raman experiments show that its blue chromophore arises from a (mu-1,2-peroxo)diiron(III) center that forms in the reaction of the reduced enzyme with O2, so the peroxo form of hDOHH is unusually stable. Nevertheless we demonstrate that it can carry out the hydroxylation of the deoxyhypusine residue present in the elF5A substrate. Despite a lack of sequence similarity, hDOHH has a nonheme diiron active site that resembles both in structure and function those found in methane and toluene monooxygenases, bacterial and mammalian ribonucleotide reductases, and stearoyl acyl carrier protein Delta9-desaturase from plants, suggesting that the oxygen-activating diiron motif is a solution arrived at by convergent evolution. Notably, hDOHH is the only example thus far of a human hydroxylase with such a diiron active site.